Low-grade serous ovarian carcinoma (LGSOC) is a rare tumor subtype with high case fatality rates in patients with metastatic disease. There is a pressing need to develop effective treatments using newly available preclinical models for therapeutic discovery and drug evaluation. Here we use multiomics integration of whole exome sequencing, RNA sequencing, and mass spectrometry-based proteomics on fourteen LGSOC cell lines to elucidate novel biomarkers and therapeutic vulnerabilities. Comparison of LGSOC cell line data to LGSOC tumor data enabled predictive biomarker identification of MEK inhibitor (MEKi) efficacy, with KRAS mutations found exclusively in MEKi-sensitive cell lines and NRAS mutations found mostly in MEKi-resistant cell lines. Distinct patterns of COSMIC mutational signatures were identified in MEKi-sensitive and MEKi-resistant cell lines. Deletions of CDKN2A/B and MTAP genes were more frequent in cell lines than tumor samples and possibly represent key driver events in the absence of KRAS/NRAS/BRAF mutations. These LGSOC cell lines were representative models of the molecular aberrations found in LGSOC tumors. For prediction of in vitro MEKi efficacy, proteomic data provided better discrimination than gene expression data. Condensin, MCM, and RFC protein complexes were identified as potential treatment targets in MEKi-resistant cell lines. This study suggests that CDKN2A/B or MTAP deficiency may be exploited using synthetically lethal treatment strategies, highlighting the importance of using proteomic data as a tool for molecular drug prediction. Multiomics approaches are crucial to improving our understanding of the molecular underpinnings of LGSOC and applying this information to develop new therapies.
Context: Genomic stratification can impact prostate cancer (PC) care through diagnostic, prognostic, and predictive biomarkers that aid in clinical decision-making. The temporal and spatial genomic heterogeneity of PC together with the challenges of acquiring metastatic tissue biopsies hinder implementation of tissue-based molecular profiling in routine clinical practice. Blood-based liquid biopsies are an attractive, minimally invasive alternative.
Objective: To review the clinical value of blood-based liquid biopsy assays in PC and identify potential applications to accelerate the development of precision medicine.
Evidence acquisition: A systematic review of PubMed/MEDLINE was performed to identify relevant literature on blood-based circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and extracellular vesicles (EVs) in PC.
Evidence synthesis: Liquid biopsy has emerged as a practical tool to profile tumor dynamics over time, elucidating features that evolve (genome, epigenome, transcriptome, and proteome) with tumor progression. Liquid biopsy tests encompass analysis of DNA, RNA, and proteins that can be detected in CTCs, ctDNA, or EVs. Blood-based liquid biopsies have demonstrated promise in the context of localized tumors (diagnostic signatures, risk stratification, and disease monitoring) and advanced disease (response/resistance biomarkers and prognostic markers).
Conclusions: Liquid biopsies have value as a source of prognostic, predictive, and response biomarkers in PC. Most clinical applications have been developed in the advanced metastatic setting, where CTC and ctDNA yields are significantly higher. However, standardization of assays and analytical/clinical validation is necessary prior to clinical implementation.
Patient summary: Traces of tumors can be isolated from blood samples from patients with prostate cancer either as whole cells or as DNA fragments. These traces provide information on tumor features. These minimally invasive tests can guide diagnosis and treatment selection.
Molecular stratification can improve the management of advanced cancers, but requires relevant tumor samples. Metastatic urothelial carcinoma (mUC) is poised to benefit given a recent expansion of treatment options and its high genomic heterogeneity. We profile minimally-invasive plasma circulating tumor DNA (ctDNA) samples from 104 mUC patients, and compare to same-patient tumor tissue obtained during invasive surgery. Patient ctDNA abundance is independently prognostic for overall survival in patients initiating first-line systemic therapy. Importantly, ctDNA analysis reproduces the somatic driver genome as described from tissue-based cohorts. Furthermore, mutation concordance between ctDNA and matched tumor tissue is 83.4%, enabling benchmarking of proposed clinical biomarkers. While 90% of mutations are identified across serial ctDNA samples, concordance for serial tumor tissue is significantly lower. Overall, our exploratory analysis demonstrates that genomic profiling of ctDNA in mUC is reliable and practical, and mitigates against disease undersampling inherent to studying archival primary tumor foci. We urge the incorporation of cell-free DNA profiling into molecularly-guided clinical trials for mUC.
Purpose: DNA damage repair (DDR) defects are common across cancer types and can indicate therapeutic vulnerability. Optimal exploitation of DDR defects in prostate cancer requires new diagnostic strategies and a better understanding of associated clinical-genomic features.
Experimental design: We performed targeted sequencing of 1615 plasma cell-free DNA samples from 879 metastatic prostate cancer patients. Depth-based copy-number calls and heterozygous SNP imbalance were leveraged to expose DDR-mutant allelic configuration and categorize mechanisms of biallelic loss. We used split-read structural variation analysis to characterize tumor suppressor rearrangements. Patient-matched archival primary tissue was analyzed identically.
Results: BRCA2, ATM, and CDK12 were the most frequently disrupted DDR genes in circulating tumor DNA (ctDNA), collectively mutated in 15% of evaluable cases. Biallelic gene disruption via second somatic alteration or mutant-allele specific imbalance was identified in 79% of patients. A further 2% exhibited homozygous BRCA2 deletions. Tumor suppressors TP53, RB1, and PTEN were controlled via disruptive chromosomal rearrangements in BRCA2-defective samples, but via oncogene amplification in context of CDK12 defects. TP53 mutations were rare in cases with ATM defects. DDR mutations were redetected across 94% of serial ctDNA samples and in all available archival primary tissues, indicating they arose prior to metastatic progression. Loss of BRCA2 and CDK12-but not ATM-was associated with poor clinical outcomes.
Conclusions: BRCA2, ATM, and CDK12 defects are each linked to distinct prostate cancer driver genomics and aggression. The consistency of DDR status in longitudinal samples and resolution of allelic status underscores the potential for ctDNA as a diagnostic tool.
A popular notion about experiments is that it is beneficial to reduce subjects’ biological and environmental variability to mitigate the influence of confounding factors on the response. The argument is that by keeping the levels of such factors fixed — a process called standardization — we increase precision by limiting the component of response variance that is not due to the experimental treatment. Unfortunately, although standardization increases power, it can also induce such unrealistically low variability that the results do not generalize to the population of interest and may thus be irreproducible — the so-called “standardization fallacy”1. This month, we show how to avoid this fallacy by balancing standardization, which increases power to detect an effect but reduces external validity, with controlled heterogenization, which may reduce power but increases external validity.
Background: RNA-sequencing-based classifiers can stratify pancreatic ductal adenocarcinoma (PDAC) into prognostically significant subgroups but are not practical for use in clinical workflows. Here, we assess whether histomorphological features may be used as surrogate markers for predicting molecular subgroup and overall survival in PDAC.
Methods: Ninety-six tissue samples from 50 patients with non-resectable PDAC were scored for gland formation, stromal maturity, mucin, necrosis, and neutrophil infiltration. Prognostic PDAC gene expression classifiers were run on all tumors using whole transcriptome sequencing data from the POG trial (NCT02155621). Findings were validated using digital TCGA slides (n = 50). Survival analysis used multivariate Cox proportional-hazards tests and log-rank tests.
Results: The combination of low gland formation and low neutrophil infiltration was significantly associated with the poor prognosis PDAC molecular subgroup (basal-like or squamous) and was an independent predictor of shorter overall survival, in both frozen section (n = 47) and formalin-fixed paraffin-embedded (n = 49) tissue samples from POG patients, and in the TCGA samples. This finding held true in the subgroup analysis of primary (n = 17) and metastatic samples (n = 79). The combination of high gland formation and high neutrophils had low sensitivity but high specificity for favorable prognosis subgroups.
Conclusions: The assessment of gland formation and neutrophil infiltration on routine histological sections can aid in prognostication and allow inferences to be made about molecular subtype, which may help guide patient management decisions and contribute to our understanding of heterogeneity in treatment response.
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Androgen deprivation therapy (ADT) remains the backbone therapy for the treatment of metastatic hormone-sensitive prostate cancer (mHSPC). In recent years, several treatments, including docetaxel, abiraterone + prednisone, enzalutamide, and apalutamide, have each been shown to demonstrate survival benefit when used upfront along with ADT. However, treatment selection for an individual patient remains a challenge. There is no high level clinical evidence for treatment selection among these choices based on biological drivers of clinical disease. In August 2020, the Prostate Cancer Foundation convened a working group to meet and discuss biomarkers for hormone-sensitive prostate cancer, the proceedings of which are summarized here. This meeting covered the state of clinical and biological evidence for systemic therapies in the mHSPC space, with emphasis on charting a course for the generation, interrogation, and clinical implementation of biomarkers for treatment selection.
Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare and aggressive form of ovarian cancer. SCCOHT tumors have inactivating mutations in SMARCA4 (BRG1), one of the two mutually exclusive ATPases of the SWI/SNF chromatin remodeling complex. To address the role that BRG1 loss plays in SCCOHT tumorigenesis, we performed integrative multi-omic analyses in SCCOHT cell lines +/- BRG1 re-expression. BRG1 re-expression induced a gene and protein signature similar to an epithelial cell and gained chromatin accessibility sites correlated with other epithelial originating TCGA tumors. Gained chromatin accessibility and BRG1 recruited sites were strongly enriched for transcription factor binding motifs of AP-1 family members. Furthermore, AP-1 motifs were enriched at the promoters of highly upregulated epithelial genes. Using a dominant negative AP-1 cell line, we found that both AP-1 DNA binding activity and BRG1 re-expression are necessary for the gene and protein expression of epithelial genes. Our study demonstrates that BRG1 re-expression drives an epithelial-like gene and protein signature in SCCOHT cells that depends upon by AP-1 activity.
Purpose: Gene fusions are important oncogenic drivers and many are actionable. Whole-genome and transcriptome (WGS and RNA-seq, respectively) sequencing can discover novel clinically relevant fusions.
Experimental design: Using WGS and RNA-seq, we reviewed the prevalence of fusions in a cohort of 570 patients with cancer, and compared prevalence to that predicted with commercially available panels. Fusions were annotated using a consensus variant calling pipeline (MAVIS) and required that a contig of the breakpoint could be constructed and supported from ≥2 structural variant detection approaches.
Results: In 570 patients with advanced cancer, MAVIS identified 81 recurrent fusions by WGS and 111 by RNA-seq, of which 18 fusions by WGS and 19 by RNA-seq were noted in at least 3 separate patients. The most common fusions were EML4-ALK in thoracic malignancies (9/69, 13%), and CMTM8-CMTM7 in colorectal cancer (4/73, 5.5%). Combined genomic and transcriptomic analysis identified novel fusion partners for clinically relevant genes, such as NTRK2 (novel partners: SHC3, DAPK1), and NTRK3 (novel partners: POLG, PIBF1).
Conclusions: Utilizing WGS/RNA-seq facilitates identification of novel fusions in clinically relevant genes, and detected a greater proportion than commercially available panels are expected to find. A significant benefit of WGS and RNA-seq is the innate ability to retrospectively identify variants that becomes clinically relevant over time, without the need for additional testing, which is not possible with panel-based approaches.
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The practical application of genome-scale technologies to precision oncology research requires flexible tissue processing strategies that can be used to differentially select both tumour and normal cell populations from formalin-fixed, paraffin-embedded tissues. As tumour sequencing scales towards clinical implementation, practical difficulties in scheduling and obtaining fresh tissue biopsies at scale, including blood samples as surrogates for matched 'normal' DNA, have focused attention on the use of formalin-preserved clinical samples collected routinely for diagnostic purposes. In practice, such samples often contain both tumour and normal cells which, if correctly partitioned, could be used to profile both tumour and normal genomes, thus identifying somatic alterations. Here we report a semi-automated method for laser microdissecting entire slide-mounted tissue sections to enrich for cells of interest with sufficient yield for whole genome and transcriptome sequencing. Using this method, we demonstrated enrichment of tumour material from mixed tumour-normal samples by up to 67%. Leveraging new methods that allow for the extraction of high-quality nucleic acids from small amounts of formalin-fixed tissues, we further showed that the method was successful in yielding sequence data of sufficient quality for use in BC Cancer's Personalized OncoGenomics (POG) program.